Today mobile broadband traffic is exploding in cellular networks such as, for example, WCDMA (Wideband Code Division Multiple Access) networks. A technical consequence is a corresponding steep increase of interference in these networks, or equivalently, a steep increase of a load. This makes it important to exploit any load headroom that is left in the most efficient way.
Moreover, cellular networks are becoming more heterogeneous, with macro radio base stations (RBSs) being supported by micro and pico RBSs at traffic hot spots. Also, home base stations (femto RBSs) are emerging in many networks.
Heterogeneous networks (HetNets) concern effects associated with networks where different kinds of cells are mixed. These cells may have different radio properties in terms of e.g.                Radio sensitivity        Frequency band        Coverage        Output power        Capacity        Acceptable load level.        
This can be an effect of a use of different RBS sizes (macro, micro, pico, femto), different revisions (different receiver technology, software quality), different vendors and of the purpose of a specific deployment.
One important factor in HetNets is that of air interface load management, i.e. the issues associated with the scheduling of radio resources in different cells and the interaction between cells in terms of inter-cell interference. Hereinafter, the terms inter-cell interference and neighbor cell interference will be used interchangeably.
As an example, one can consider a low power cell with limited coverage intended to serve a hotspot. In order to get a sufficient coverage of the hot spot, an interference suppressing receiver like the G-rake+ may be used. The low power cell may further be located in the interior of but still close to a boundary of a specific macro cell. Further, surrounding macro cells will interfere with the low power cell rendering a high level of neighbor cell interference in the low power cell. Despite the advanced receiver, this may unacceptably reduce the coverage in the hot spot. As a result, users of the hot spot tend to connect to the surrounding macro cells instead, thereby further increasing the neighbor cell interference experienced by the low power cell.
From this discussion it should be clear that it would be advantageous if a control node, such as a radio network controller (RNC) or the surrounding RBSs could be informed of an interference situation and take action, using e.g. admission control in the RNC or new functionality in the surrounding RBSs to reduce inter-cell interference and to provide a better management of, for example, hot spot traffic—in terms of air interface load.
It follows that estimation of the neighbour cell interference at a node such as an RBS is a crucial component in the handling of interference.
Neighbor cell interference estimation as such based on uplink power measurements is, for example, described in T. Wigren, “Soft uplink load estimation in WCDMA”, IEEE Trans Veh. Tech., March, 2009; and in WO2007/024166; and also in U.S. Pat. No. 7,912,461.
These teachings rely on estimation by means of a high order vector estimator of a Kalman filtering type. Kalman filtering is a specific type of algorithm useful when filtering is performed on dynamic systems modelled by state vectors. For example, Kalman filtering is optimal when a dynamic state model is linear and when an input signal can be modelled with Gaussian stochastic processes. However, this results in a very high computational complexity, which puts a corresponding high demand on processing power in the RBSs.
With the above-mentioned HetNet trend, a significant parameter is a cost of the new smaller nodes. In particular, implementation of new functionality, such as support of interference control, needs to be done without a need for excessive processing power in the nodes.
Consequently, there is a need for a provision of ways and means for reduction of the processing demand associated with neighbor cell interference handling/estimation.